How to set up an Auto Scaling Group with target tracking on CPU
| Service | Amazon EC2 |
|---|---|
| Cloud | Amazon Web Services (AWS) |
| Guide type | Procedure |
| Skill level | Intermediate to advanced |
| Time | 15 - 60 minutes depending on account size |
Engineers running Amazon EC2 hit How to set up an Auto Scaling Group with target tracking on CPU often enough that there is a stable fix pattern. This page captures it in the order AWS support would run it during a real incident.
What how to set up an auto scaling group with target tracking on cpu actually involves on Amazon EC2
This task on EC2 is one of the more searched operational topics on AWS in the last 12 months. The procedure below is the path that works in a current AWS account with default IAM and standard VPC config.
The rest of this page is the structured fix path. Start with diagnose, then remediation, then the automation options so you do not have to do this by hand the next time it surfaces. Verify and safety sections at the end are the discipline that keeps the fix from regressing in production.
What you'll see
Diff against last known good. The last config change you made is the cause about three quarters of the time, even when the change should not have mattered. Use AWS Config history (or your Terraform / CloudFormation drift report) to see the actual delta between the resource state when it worked and when it broke. The change you remember is often not the only change that happened.
Reproduce the failure with the AWS CLI in --debug mode. The full SigV4 request payload it emits, plus the exact endpoint URL it resolved to, is what AWS Support uses to verify policy, region, or parameter issues without you having to share IAM credentials. Save the debug output to a file with aws ... --debug 2> debug.log and you can search it for the failed aws.request entry.
Look at the CloudTrail event for the failed call, even if you are not enrolled in CloudTrail Lake. The basic 90-day event history works for most diagnostic purposes and lives in the console under CloudTrail > Event history. Filter by event name (the API action) and time range; the event JSON shows the exact user identity, source IP, request parameters, and error code.
Solution-focused remediation path
If networking is suspect, use VPC Reachability Analyzer. It is the only tool that simulates the full ENI-to-ENI path including security groups, NACLs, route tables, and VPC endpoint policies in one call. Manual trace is slower and misses transitive issues. The analyzer charges $0.10 per analysis - cheaper than a 30-minute call with your network team.
Most Amazon EC2 failures fall into one of three buckets: IAM permission gap, networking path break (security group, NACL, or VPC endpoint policy), or service-limit / quota hit. Run that mental triage first - it covers around 80 percent of real-world cases. If the failure does not fit any of the three, it is likely a service-side regression worth opening a re:Post or support ticket for.
If quotas are suspect, the Service Quotas console shows current usage and the active limit side by side. Request increases through Service Quotas, not through Support tickets - quota dashboard requests usually approve faster (often within minutes for soft limits) and they are auditable in CloudTrail. Set up Service Quotas + CloudWatch alarms at 80 percent usage so you get notified before you hit the wall.
Automate this fix so you do not do it twice
Wire the fix into EventBridge for self-healing
If the failure mode is recurring, automate the remediation instead of the diagnosis. EventBridge Scheduler or rules that watch CloudWatch Events for the specific error code can invoke a Lambda that runs the same fix you would run by hand. The Lambda must be idempotent (re-running it on already-healthy resources must be a no-op) and must emit a CloudWatch metric so you can track how often the auto-fix fires. A spike in auto-fix invocations is itself a signal worth alerting on.
# EventBridge rule pattern (JSON)
{ "source": ["aws.ec2"], "detail-type": ["AWS API Call via CloudTrail"], "detail": { "errorCode": ["AccessDenied", "ThrottlingException"] }
}Add a CloudWatch alarm so you know next time
The cheapest way to never see the same incident twice is a CloudWatch alarm on the metric that would have warned you. For Amazon EC2, the relevant metrics live under AWS/ec2 namespace or under custom metrics published by your Lambda or ECS task. Set thresholds based on observed normal range plus one or two standard deviations, not on round-number guesses. CloudWatch anomaly-detection alarms remove the threshold-guessing problem entirely for metrics with regular seasonality.
Automate the fix with the AWS CLI
The CLI one-liner pattern for Amazon EC2 operations is roughly: aws ec2 describe-... --query ... to read state, aws ec2 modify-... --no-dry-run to apply the change, and aws ec2 describe-... --query ... again to verify. Wrap it in a shell script that sets a region variable at the top and exits on first error with set -euo pipefail so a partial run does not leave the account in a half-fixed state.
# Template - replace placeholders with your account specifics
export AWS_REGION=us-east-1
export AWS_PROFILE=prod
aws ec2 describe-... --query 'Resources[?Status==`FAILED`].[Id,Reason]' --output table
aws ec2 modify-... --resource-id RESOURCE_ID --no-dry-run
aws ec2 describe-... --resource-id RESOURCE_ID --query 'Status'
Common traps
A subtle pitfall on Amazon EC2 is that the AWS Console and the SDK can disagree about resource state during a configuration change. Console UI is cached for performance and may show the old config for up to 10 minutes after you change it via API or CloudFormation. Always confirm with describe-* CLI calls during a change window, not with screenshots from the Console.
The other pitfall: assuming that an automated remediation is correct because it succeeded. A Lambda that fires on a CloudWatch alarm and runs a remediation step should also publish a metric for every remediation; sudden surges in auto-fix invocations are themselves an outage signal. Otherwise you can hide a slow-burn regression behind a quiet remediation loop for weeks.
The repair
- Reproduce the original symptom path. If it still surfaces in any account or region or IAM role, you have not fixed it.
- Watch for 24 to 48 hours. AWS metrics and policy systems can mask issues with cached health for 6 to 12 hours, especially CloudFront and Route 53.
- Run a smoke test under realistic load. Happy-path tests miss race conditions and IAM session-cache issues.
- Capture the new state in a runbook so the next person on call does not have to rediscover this. Push it to Confluence or your team wiki, not into Slack.
- If the fix involved a permission change, run IAM Access Analyzer one more time to confirm you did not open a separate hole while closing this one.
Safety, rollback, blast radius
- Test in a non-production account if your environment has Control Tower or AWS Organizations. The cost of one sandbox account is cheaper than one rollback meeting.
- Export the existing config before changing it. Most Amazon EC2 resources support describe + export to JSON via CLI - capture that to source control before you start.
- Know your rollback path. Some Amazon EC2 operations are one-way (region migration, account-level feature opt-in, KMS key deletion past pending window). Confirm reversibility on the AWS doc before you commit.
- Be aware of cross-service impact. IAM role changes ripple to every service trusting that role. KMS key changes break every workload depending on that key. VPC endpoint changes affect every VPC consumer of that endpoint.
- Maintenance window discipline: if the change touches DNS, certificate rotation, or anything that emits TLS handshakes, line up a window with stakeholder notification, not a heroic mid-day swap.
FAQ
aws ec2 describe-... first, then commit it before you change anything. A few operations are one-way (KMS key deletion past the pending window, region migration, account closure). Check the AWS doc for the specific API before you commit.aws CLI or SDK calls - those almost always still work.References
- docs.aws.amazon.com - official documentation for Amazon EC2
- AWS re:Post (formerly forums) - community Q&A with AWS-staff-verified answers
- AWS Health Dashboard at health.aws.amazon.com
- AWS Service Quotas console and AWS Well-Architected Tool
Related fixes
Related guides worth a look while you sort this one out:
- How to set up ECS service Auto Scaling with target tracking
- How to create a launch template with user data for Auto Scaling Group
- How to fix EC2 Auto Scaling Group not scaling out under load
- How to mix Spot and On-Demand in an Auto Scaling Group
- How to set up a Dedicated Host for BYOL Windows or Oracle workloads
- Aurora storage auto-scaling and the 128 TiB ceiling